Faraday Discussions最新文献

The prediction of new compounds via crystal structure prediction may transform how the materials chemistry community discovers new compounds. In the prediction of inorganic crystal structures there are three distinct classes of prediction: performing crystal structure prediction via heuristic algorithms, using a range of established crystal structure prediction codes, an emerging community using generative machine learning models to predict crystal structures directly and the use of mathematical optimisation to solve crystal structures exactly. In this work, we demonstrate the combination of heuristic and generative machine learning, the use of a generative machine learning model to produce the starting population of crystal structures for a heuristic algorithm and discuss the benefits, demonstrating the method on eight known compounds with reported crystal structures and three hypothetical compounds. We show that the integration of machine learning structure generation with heuristic structure prediction results in both faster compute times per structure and lower energies. This work provides to the community a set of eleven compounds with varying chemistry and complexity that can be used as a benchmark for new crystal structure prediction methods as they emerge.

Hydrophobic non-ionic (type V) deep eutectic solvents (DESs) have recently emerged as a new class of sustainable materials that have shown unique properties in several applications. In this study, type V DESs thymol : camphor, menthol : thymol and eutectic mixtures (EMs) based on menthol : carboxylic acids with variable chain length, are experimentally investigated using xenon NMR spectroscopy, with the aim to clarify the peculiar nanostructure of these materials. The results, obtained from the analysis of the ¹²⁹Xe chemical shifts and of the longitudinal relaxation times, reveal a correlation between the deviation from ideality of the DESs and their structure free volume. Furthermore, the effect of varying the composition of DESs and EMs on the liquid structure is also studied.

Ion adsorption and dynamics in porous carbons are crucial for many technologies, such as energy storage and desalination. Nuclear magnetic resonance (NMR) spectroscopy is a key method to investigate such systems thanks to the possibility of distinguishing adsorbed (in-pore) and bulk (ex-pore) species in the spectra. However, the large variety of magnetic environments experienced by the ions adsorbed in the particles and the existence of dynamic exchange between the inside of the particles and the bulk renders the interpretation of the NMR experiments very complex. In this work, we optimise and apply a mesoscopic model to simulate NMR spectra of ions in systems where carbon particles of different sizes can be considered. We demonstrate that even for monodisperse systems, complex NMR spectra, with broad and narrow peaks, can be observed. We then show that the inclusion of polydispersity is essential to recover some experimentally observed features, such as the co-existence of peaks assigned to in-pore, exchange and bulk species. Indeed, the variety of exchange rates between in-pore and ex-pore environments, present in experiments but not taken into account in analytical models, is necessary to reproduce the complexity of experimental NMR spectra.

Supramolecular hydrogels have a wide range of applications in the biomedical field, acting as scaffolds for cell culture, matrices for tissue engineering and vehicles for drug delivery. L-Phenylalanine (Phe) is a natural amino acid that plays a significant role in several physiological and pathophysiological processes (phenylketonuria and assembly of fibrils linked to tissue damage). Since Myerson et al. [Chem. Eng. Commun., 2002, 189(8), 1079–1090] reported that Phe forms a fibrous network in vitro, Phe's self-assembly processes in water have been thoroughly investigated. We have reported structural control over gelation by introduction of a halogen atom in the aromatic ring of Phe, driving changes in the packing motifs, and therefore, dictating gelation functionality. The additional level of control gained over supramolecular gelation via the preparation of multi-component gel systems offers significant advantages in tuning functional properties of such materials. Gaining molecular-level information on the distribution of gelators between the inherent structural and dynamic heterogeneities of these materials remains a considerable challenge. Using multicomponent gels based on Phe and amino-L-phenylalanine (NH₂-Phe), we will explore the patterns of ordered/disordered domains in the gel fibres and will attempt to come up with general trends of interactions in the gel fibres and at the fibre/solution interfaces. Phe and NH₂-Phe were found to self-assemble in water into crystalline hydrogels. The determined faster dynamics of exchange between the gel and solution states of NH₂-Phe in comparison with Phe were correlated with weaker intermolecular interactions, highlighting the role of head groups in dictating the strength of intermolecular interactions. In the mixed Phe/NH₂-Phe systems, at a low concentration of NH₂-Phe, disruption of the network was promoted by interference of the aliphatics of NH₂-Phe with the electrostatic interactions between Phe molecules. At high concentrations of NH₂-Phe, multiple-gelator hydrogels were formed with crystal habits different from those of the pure gel fibres. NMR crystallography approaches combining the strengths of solid- and solution-state NMR proved particularly suitable to obtain structural and dynamic insights into the “ordered” fibres, solution phase and fibre/solution interfaces in these gels. These findings are supported by a plethora of experimental (diffraction, rheology, microscopy and thermal analysis) and computational methods.

Here we examine the question of the chemical models widely used to describe dense solutions, particularly ionic solutions. First, a simple macroscopic analysis shows that, in the case of weak interactions, taking into account aggregated species amounts to modelling an effective attraction between solutes, although the stoichiometry used does not necessarily correspond to atomic reality. We then use a rigorous microscopic analysis to explain how, in the very general case, chemical models can be obtained from an atomic physical description. We show that there are no good or bad chemical models as long as we consider exact calculations. To obtain the simplest possible description, it is nevertheless advisable to take the speciation criterion that minimises the excess terms. Molecular simulations show that, very often, species can be defined simply by grouping ions which are in direct contact. In some cases, the appearance of macroscale clusters can be predicted.

We developed a general theoretical approach and a user-ready computer code that permit study of the dynamics of collisional energy transfer and ro-vibrational energy exchange in complex molecule–molecule collisions. The method is a mixture of classical and quantum mechanics. The internal ro-vibrational motion of collision partners is treated quantum mechanically using a time-dependent Schrödinger equation that captures many quantum phenomena including state quantization and zero-point energy, propensity and selection rules for state-to-state transitions, quantum symmetry and interference phenomena. A significant numerical speed up is obtained by describing the translational motion of collision partners classically, using the Ehrenfest mean-field trajectory approach. Within this framework a family of approximate methods for collision dynamics is developed. Several benchmark studies for diatomic and triatomic molecules, such as H₂O and ND₃ collided with He, H₂ and D₂, show that the results of MQCT are in good agreement with full-quantum calculations in a broad range of energies, especially at high collision energies where they become nearly identical to the full quantum results. Numerical efficiency of the method and massive parallelism of the MQCT code permit us to embrace some of the most complicated collisional systems ever studied, such as C₆H₆ + He, CH₃COOH + He and H₂O + H₂O. Application of MQCT to the collisions of chiral molecules such as CH₃CHCH₂O + He, and to molecule–surface collisions is also possible and will be pursued in the future.

The exploration of the fundamental formation mechanisms of polycyclic aromatic hydrocarbons (PAHs) is crucial for the understanding of molecular mass growth processes leading to two- and three-dimensional carbonaceous nanostructures (nanosheets, graphenes, nanotubes, buckyballs) in extraterrestrial environments (circumstellar envelopes, planetary nebulae, molecular clouds) and combustion systems. While key studies have been conducted exploiting traditional, high-temperature mechanisms such as the hydrogen abstraction–acetylene addition (HACA) and phenyl addition–dehydrocyclization (PAC) pathways, the complexity of extreme environments highlights the necessity of investigating chemically diverse mass growth reaction mechanisms leading to PAHs. Employing the crossed molecular beams technique coupled with electronic structure calculations, we report on the gas-phase synthesis of phenanthrene (C₁₄H₁₀)—a three-ring, 14π benzenoid PAH—via a phenylethynyl addition–cyclization–aromatization mechanism, featuring bimolecular reactions of the phenylethynyl radical (C₆H₅CC, X²A₁) with benzene (C₆H₆) under single collision conditions. The dynamics involve a phenylethynyl radical addition to benzene without entrance barrier leading eventually to phenanthrene via indirect scattering dynamics through C₁₄H₁₁ intermediates. The barrierless nature of reaction allows rapid access to phenanthrene in low-temperature environments such as cold molecular clouds which can reach temperatures as low as 10 K. This mechanism constitutes a unique, low-temperature framework for the formation of PAHs as building blocks in molecular mass growth processes to carbonaceous nanostructures in extraterrestrial environments thus affording critical insight into the low-temperature hydrocarbon chemistry in our universe.

The application of NMR crystallography to organic molecules is exemplified by two case studies. For the tosylate salt of the active pharmaceutical ingredient, Ritlectinib, solid-state NMR spectra are presented at a ¹H Larmor frequency of 1 GHz and a magic-angle spinning (MAS) frequency of 60 kHz. Specifically, ¹⁴N–¹H heteronuclear multiple-quantum coherence (HMQC) and ¹H–¹H double-quantum (DQ) single-quantum (SQ) correlation experiments are powerful probes of hydrogen bonding interactions. A full assignment of the ¹H, ¹³C and ¹⁴N/¹⁵N chemical shifts is achieved using also ¹H–¹³C cross polarization (CP) HETCOR spectra together with gauge-including projector augmented wave (GIPAW) DFT calculation for the geometry-optimised X-ray diffraction crystal structure that is reported here (CCDC 2352028). In addition, GIPAW calculations are presented for the ¹³C chemical shifts in the two polymorphs of cellulose for which diffraction structures are available. For both case studies, a focus is on the discrepancy between experiment and GIPAW calculation.

The controlled activation of methane has drawn significant attention throughout various disciplines over the last few decades. In gas-phase experiments, the use of model systems with reduced complexity compared to condensed-phase catalytic systems allows us to investigate the intrinsic reactivity of elementary reactions down to the atomic level. Methane is rather inert in chemical reactions, as the weakening or cleavage of a C–H bond is required to make use of methane as C₁-building block. The simplest model system for transition-metal-based catalysts is a mono-atomic metal ion. Only a few atomic transition-metal cations activate methane at room temperature. One of the most efficient elements is tantalum, which forms a carbene and releases molecular hydrogen in the reaction with methane: Ta⁺ + CH₄ → TaCH₂⁺ + H₂. The reaction takes place at room temperature due to efficient intersystem crossing from the quintet to the triplet surface, i.e., from the electronic ground state of the tantalum cation to the triplet ground state of the tantalum carbene. This multi-state reactivity is often seen for reactions involving transition-metal centres, but leads to their theoretical treatment being a challenge even today. Chemical reactions, or to be precise reactive collisions, are dynamic processes making their description even more of a challenge to experiment and theory alike. Experimental energy- and angle-differential cross sections allow us to probe the rearrangement of atoms during a reactive collision. By interpreting the scattering signatures, we gain insight into the atomistic mechanisms and can move beyond stationary descriptions. Here, we present a study combining collision energy dependent experimentally measured differential cross sections with ab initio calculations of the minimum energy pathway. Product ion velocity distributions were recorded using our crossed-beam velocity map imaging experiment dedicated to studying transition-metal ion molecule reactions. TaCH₂⁺ velocity distributions reveal a significant degree of indirect dynamics. However, the scattering distributions also show signatures of rebound dynamics. We compare the present results to the oxygen transfer reaction between Ta⁺ and carbon dioxide, which we recently studied.

In bimolecular collisions between open-shell radicals and increasingly-larger alkanes, the relative impact configurations open the possibility of reactive and nonreactive outcomes that are isomer specific. To model the interaction potential between molecular scattering partners, observables are needed from experiments that can quantify both the initial molecular orientations and internal energies on multidimensional potential energy surfaces. Recent work by our group demonstrated that upon infrared (IR) excitation, the dynamics of the nitric oxide–methane collision complex (NO–CH₄) are dependent on the initial monomer geometries, as small changes in configuration substantially affect the energies, electronic couplings, and predissociation pathways due to the Jahn–Teller effect. This study focuses on the isomer-specific scattering mechanisms between NO and ethane (C₂H₆), encoded in the spectroscopic and dynamical signatures of the NO–C₂H₆ collision complex. IR action spectroscopy with 1 + 1 resonance-enhanced multiphoton ionization of NO products was employed to characterize the fundamental CH stretch transitions of NO–C₂H₆, as well as to initiate the nonreactive decay mechanisms of the complex. Furthermore, velocity map imaging (VMI) was utilized to explore the dynamics prior to and following IR excitation of NO–C₂H₆, imprinted on the NO photoproducts. This work compares the dynamics from NO–C₂H₆ and NO–CH₄ vibrational predissociation, in which substantial differences are observed in the energy exchange mechanisms during the evolution of the collision complexes to products.